From 221fee3a8a5c14ed15be3b8bc6cbacb587380424 Mon Sep 17 00:00:00 2001 From: vanesm Date: Sun, 15 Dec 2024 16:06:45 -0500 Subject: [PATCH 1/3] fixing error with dataframe size --- StudentData/PIXL_LIBS_Combined.Rds | Bin 33792 -> 48305 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/StudentData/PIXL_LIBS_Combined.Rds b/StudentData/PIXL_LIBS_Combined.Rds index c7bf055c8df38e79a4e388f6ca691e4d46f42816..95f62601f74aacd1c6fa73a02dd63fc4c5f98ce4 100644 GIT binary patch literal 48305 zcmcG#cU)6h|1LUKoI#1BGom7ijxy+=L_|d-MP(Eb70W0fB`RuUD3K1SRyGxG8eS37OyP~-G*~XFI%-tS0Iiv7V1C`N%>%uV_VzV|DBVjG6 za;5;M)7MMf)tYk-4i5T|`x5eI$$NiE4w z*fVZZ|BS{03>pnnp(yQso0=b6zfpWb)DPtPJgTjr(kZ;2Id$yvG0lN-M5@-+!qU|2rjCQPB1s*6ksffOXa z$wnI;0Oo1qlb|Yt6073va~pIi)~@RmPEEJt8bG$Yx6vvB&Ae1l+d6QItrx)8YcSgo zR=<>TH9r{wdP1LhsA-0*OD+KMq%-;kb-GAjCElCVBcvURj|NpMgB>Pl+#9oOcv5WZ zRoHtuVl@r2evVj-c82^t?v~*+7rp!D$Su3nqq;cIq!0?j8@12UC9~~bZh$3-Dj1Q_ z_@1J$maaeO$8!G6>V`l(y?o7A>vLzveqLW}N|=k)7$k>jg;pGW4rNGQ2D=|K5=$SF 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zq;}z|A}HjWA*&+8DH55l>?MZPaP&NZLXQ|8Md68~H;o#DRu|g`nY8Hk#Q34J;%`ju zQrcEmt$zwPvXW}lXXBn|GHb0TR!P>%8>Iix2MkX;m{rR{%5Yl6Wz93kgb_iRYHWm^ z6`{H$6CC+mG97CX1*A~T8`3~@bZKLo5goPKRMmiTM}r3x^uHB#I!%wS3L$T11v%Bu z`y8SC;y;~6i7;`zxdTbP`ck7j+n|QVv?aA{o|cWzoE$+i-hqx5@TN(%=^1pgzC@SL zuKueM);QvfUI|m{0u*suM^`1}>b=KDe~CFlqV(!1(|27Z_!g0BwYs}ckSRGfnR?Wg}id Date: Sun, 15 Dec 2024 16:57:13 -0500 Subject: [PATCH 3/3] adding more comments and fixing merge process --- .../Assignment05/MatchingLIBSandPIXL.Rmd | 142 +++++++++--------- 1 file changed, 68 insertions(+), 74 deletions(-) diff --git a/StudentNotebooks/Assignment05/MatchingLIBSandPIXL.Rmd b/StudentNotebooks/Assignment05/MatchingLIBSandPIXL.Rmd index 7ac4ad6..d42d184 100644 --- a/StudentNotebooks/Assignment05/MatchingLIBSandPIXL.Rmd +++ b/StudentNotebooks/Assignment05/MatchingLIBSandPIXL.Rmd @@ -90,11 +90,8 @@ libs.df[,6:13] <- sapply(libs.df[,6:13],as.numeric) libs.df<-libs.df%>% filter(!(grepl("scct", target))) -#add a column to indicate the nearest pixl -libs.df<-cbind(nearestpixl=0,libs.df) - #make a dataframe of just the LIBS Lat/Long and target name and remove duplicates -libstargets.df<-libs.df[,c(1,3,4,5)] +libstargets.df<-cbind("nearestpixl"=0,libs.df[,1:4]) libstargets.df<-distinct(libstargets.df) ``` @@ -120,33 +117,24 @@ pixl.df<-pixl.df[c(2,4,6,8,10,12,14,16),] ### Combining datasets ```{r} -distance=100 -distCosine(pixl.df[1,c(1,2)],libstargets.df[1,c(2,3)], r=3393169) -for(i in 1:nrow(pixl.df)) { - libstargets.df<-libstargets.df%>%mutate(nearestpixl = ifelse(distHaversine(pixl.df[i,c(1,2)],c(lat,lon),r=3393169),pixl.df[i,5], nearestpixl)) - -} -``` - -```{r} +# Create a new dataframe with the LIBS metatdata as well as features corresponding to each PIXL Abrasion libstargets.df<-cbind(libstargets.df,"Distance"=0,"Bellegrade"=0,"Dourbes"=0,"Quartier"=0,"Alfalfa"=0,"ThorntonGap"=0,"BerryHollow"=0,"Novarupta"=0,"UganikIsland"=0) ``` ```{r} -#DistCosine(pixl.df[1,c(1,2)],libstargets.df[1,c(2,3)], r=3393169) - +#Calculate the distance between each LIBS target and each PIXL abrasion, then fill in the minimum distances for(i in 1:nrow(libstargets.df)) { - libstargets.df[i,c(6:13)]<-c(distHaversine(pixl.df[1,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[2,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[3,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[4,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[5,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[6,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[7,c(1,2)],libstargets.df[i,c(2,3)],r=3393169), - distHaversine(pixl.df[8,c(1,2)],libstargets.df[i,c(2,3)],r=3393169)) + libstargets.df[i,c(7:14)]<-c(distHaversine(pixl.df[1,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[2,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[3,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[4,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[5,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[6,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[7,c(1,2)],libstargets.df[i,c(3,4)],r=3393169), + distHaversine(pixl.df[8,c(1,2)],libstargets.df[i,c(3,4)],r=3393169)) - libstargets.df[i,1]<-which.min(libstargets.df[i,c(6:13)]) - libstargets.df[i,5]<-min(libstargets.df[i,c(6:13)]) + libstargets.df[i,1]<-which.min(libstargets.df[i,c(7:14)]) + libstargets.df[i,6]<-min(libstargets.df[i,c(7:14)]) } libstargets.df$nearestpixl<-as.factor(libstargets.df$nearestpixl) @@ -156,6 +144,7 @@ levels(libstargets.df$nearestpixl)<-(c("Bellegrade","Dourbes","Quartier","Alfalf ```{r} +#Create vectors of LIBS targets corresponding to each PIXL Abrasion Bellegrade<-libstargets.df[libstargets.df$nearestpixl=="Bellegrade",]$target Dourbes<-libstargets.df[libstargets.df$nearestpixl=="Dourbes",]$target Quartier<-libstargets.df[libstargets.df$nearestpixl=="Quartier",]$target @@ -166,26 +155,11 @@ Novarupta<-libstargets.df[libstargets.df$nearestpixl=="Novarupta",]$target UganikIsland<-libstargets.df[libstargets.df$nearestpixl=="UganikIsland",]$target ``` - -### Ternary Diagram ```{r} -meters=100 - -included.libs<-(libstargets.df%>% - filter(Distance% - filter(target %in% included.libs) - -libs.matrix <- libs.matrix[,c(5,7:14)] - -libs.tern <- as.data.frame(libs.matrix) %>% - mutate(x=(SiO2+Al2O3)/100,y=(FeOT+MgO)/100,z=(CaO+Na2O+K2O)/100) %>% - select(-c(SiO2,Al2O3,FeOT,MgO,CaO,Na2O,K2O,TiO2)) +#Add the nearest Abrasion to the LIBS data +libs.pixl.merged <- cbind("Abrasion"=0,libs.df) -libs.tern<-cbind("Abrasion"=0,libs.tern) - -libs.tern<-libs.tern%>% +libs.pixl.merged<-libs.pixl.merged%>% mutate(Abrasion = ifelse(target%in%Alfalfa,"Alfalfa", ifelse(target %in% Bellegrade, "Belegrade", ifelse(target %in% BerryHollow, "BerryHollow", @@ -193,55 +167,77 @@ libs.tern<-libs.tern%>% ifelse(target %in% Novarupta, "Novarupta", ifelse(target %in% Quartier, "Quartier", ifelse(target %in% ThorntonGap, "ThorntonGap", - ifelse(target %in% UganikIsland, "UganikIsland",Abrasion))))))))) + ifelse(target %in% UganikIsland, "Uganik Island",Abrasion))))))))) + +targetdistance<-libstargets.df[,2:6] +libs.pixl.merged<-merge(libs.pixl.merged,targetdistance,by=c("target","sol","lat","lon"),all.x=T) +``` + +```{r} +#Add back some pixl features +pix<-pixl.df[,c(1,2,4,5)] +libs.pixl <- merge(libs.pixl.merged, pix, by.x="Abrasion",by.y="abrasion",all.x=TRUE) + +#rename and reorder columns +libs.pixl<-cbind("LIBS.Target"=libs.pixl$target,libs.pixl[,4:5],"LIBS.Sol"=libs.pixl$sol,"LIBS.Point"=libs.pixl$point,"Distance"=libs.pixl$Distance,"PIXL.Abrasion"=libs.pixl$Abrasion,libs.pixl[,16:18],libs.pixl[,7:14]) +colnames(libs.pixl)<-c("LIBS.Target","LIBS.Lat","LIBS.Lon","LIBS.Sol","LIBS.Point", "Distance","PIXL.Abrasion","PIXL.Lat","PIXL.Lon","PIXL.Campaign","LIBS.SiO2","LIBS.TiO2","LIBS.Al2O3","LIBS.FeOT","LIBS.MgO","LIBS.CaO","LIBS.Na2O","LIBS.K2O") +``` -kabledf<-rbind("Distance (m)"=meters,"Targets"=length(included.libs),"Points"=nrow(libs.tern)) +```{r} +#setwd("~/DAR-Mars-F24/StudentData") +#saveRDS(libs.pixl,"PIXL_LIBS_Combined.Rds") +``` + +The libs.pixl dataframe is now saved to PIXL_LIBS_Combined.Rds, which can be found in the StudentData folder. + +### Ternary Diagram + +Example of creating a ternary plot filtering the combined LIBS and PIXL data +```{r} +libs.tern <- libs.pixl %>% + mutate(x=(LIBS.SiO2+LIBS.Al2O3)/100,y=(LIBS.FeOT+LIBS.MgO)/100,z=(LIBS.CaO+LIBS.Na2O+LIBS.K2O)/100) -kable(kabledf) +libs.tern<-libs.tern[,c(6,7,19:21)] ``` ```{r} +meters=7 + ggtern(libs.tern, ggtern::aes(x=x,y=y,z=z)) + - geom_point(data=libs.tern,aes(color=Abrasion,alpha=0.5)) + + geom_point(data=subset(libs.tern,Distance<=meters),aes(color=PIXL.Abrasion,alpha=0.5)) + theme_rgbw() + - labs(title=paste("Mars LIBS Data Within",distance,"meters of PIXL",sep=" "), + labs(title=paste("Mars LIBS Data Within",meters,"meters of PIXL",sep=" "), x="Si+Al", y="Fe+Mg", z="Ca+Na+K")+theme(legend.position="right") + guides(alpha="none") -``` - -### Line plot - -```{r} meters=100 -included.libs<-(libstargets.df%>% - filter(Distance% - filter(target %in% included.libs) +ggtern(libs.tern, ggtern::aes(x=x,y=y,z=z)) + + geom_point(data=subset(libs.tern,Distance<=meters),aes(color=PIXL.Abrasion,alpha=0.5)) + + theme_rgbw() + + labs(title=paste("Mars LIBS Data Within",meters,"meters of PIXL",sep=" "), + x="Si+Al", + y="Fe+Mg", + z="Ca+Na+K")+theme(legend.position="right") + + guides(alpha="none") +``` -libs.matrix <- libs.matrix[,c(5,7:14)] -libs.matrix<-libs.matrix[,c(1:2,4:9,3)] +### Line plot -libs.matrix<-cbind("Abrasion"=0,libs.matrix) +Example of how to add the pixl data as extra rows to the LIBS data, so that it can be graphed on the same plot -libs.matrix<-libs.matrix%>% - mutate(Abrasion = ifelse(target%in%Alfalfa,"Alfalfa", - ifelse(target %in% Bellegrade, "Belegrade", - ifelse(target %in% BerryHollow, "BerryHollow", - ifelse(target %in% Dourbes, "Dourbes", - ifelse(target %in% Novarupta, "Novarupta", - ifelse(target %in% Quartier, "Quartier", - ifelse(target %in% ThorntonGap, "ThorntonGap", - ifelse(target %in% UganikIsland, "UganikIsland",Abrasion))))))))) +```{r} +#remove certain features from the combined pixl libs dataset +libs.matrix <- libs.pixl[,c(7,1,11,13:18,12)] +#rename columns libs.matrix<-cbind(libsorpixl=1,libs.matrix) + +colnames(libs.matrix)<-c("libsorpixl","Abrasion","targets+names","SiO2","Al2O3","FeOT","MgO","CaO","Na2O","K2O","TiO2") ``` @@ -262,9 +258,7 @@ pixl.df<-cbind(libsorpixl=0,pixl.df) ``` ```{r} +#rename pixl columns and combine dataframes colnames(pixl.df)<-colnames(libs.matrix) pixllibs.df<-rbind(pixl.df,libs.matrix) ``` - - -